nixpkgs/doc/languages-frameworks/python.section.md

# Python

## User Guide

### Using Python

#### Overview

Several versions of the Python interpreter are available on Nix, as well as a
high amount of packages. The attribute `python` refers to the default
interpreter, which is currently CPython 2.7. It is also possible to refer to
specific versions, e.g. `python35` refers to CPython 3.5, and `pypy` refers to
the default PyPy interpreter.

Python is used a lot, and in different ways. This affects also how it is
packaged. In the case of Python on Nix, an important distinction is made between
whether the package is considered primarily an application, or whether it should
be used as a library, i.e., of primary interest are the modules in
`site-packages` that should be importable.

In the Nixpkgs tree Python applications can be found throughout, depending on
what they do, and are called from the main package set. Python libraries,
however, are in separate sets, with one set per interpreter version.

The interpreters have several common attributes. One of these attributes is
`pkgs`, which is a package set of Python libraries for this specific
interpreter. E.g., the `toolz` package corresponding to the default interpreter
is `python.pkgs.toolz`, and the CPython 3.5 version is `python35.pkgs.toolz`.
The main package set contains aliases to these package sets, e.g.
`pythonPackages` refers to `python.pkgs` and `python35Packages` to
`python35.pkgs`.

#### Installing Python and packages

The Nix and NixOS manuals explain how packages are generally installed. In the
case of Python and Nix, it is important to make a distinction between whether the
package is considered an application or a library.

Applications on Nix are typically installed into your user
profile imperatively using `nix-env -i`, and on NixOS declaratively by adding the
package name to `environment.systemPackages` in `/etc/nixos/configuration.nix`.
Dependencies such as libraries are automatically installed and should not be
installed explicitly.

The same goes for Python applications and libraries. Python applications can be
installed in your profile. But Python libraries you would like to use for
development cannot be installed, at least not individually, because they won't
be able to find each other resulting in import errors. Instead, it is possible
to create an environment with `python.buildEnv` or `python.withPackages` where
the interpreter and other executables are able to find each other and all of the
modules.

In the following examples we create an environment with Python 3.5, `numpy` and
`toolz`. As you may imagine, there is one limitation here, and that's that
you can install only one environment at a time. You will notice the complaints
about collisions when you try to install a second environment.

##### Environment defined in separate `.nix` file

Create a file, e.g. `build.nix`, with the following expression
```nix
with import <nixpkgs> {};

python35.withPackages (ps: with ps; [ numpy toolz ])
```
and install it in your profile with
```shell
nix-env -if build.nix
```
Now you can use the Python interpreter, as well as the extra packages (`numpy`,
`toolz`) that you added to the environment.

##### Environment defined in `~/.config/nixpkgs/config.nix`

If you prefer to, you could also add the environment as a package override to the Nixpkgs set, e.g.
using `config.nix`,
```nix
{ # ...

  packageOverrides = pkgs: with pkgs; {
    myEnv = python35.withPackages (ps: with ps; [ numpy toolz ]);
  };
}
```
and install it in your profile with
```shell
nix-env -iA nixpkgs.myEnv
```
The environment is is installed by referring to the attribute, and considering
the `nixpkgs` channel was used.

##### Environment defined in `/etc/nixos/configuration.nix`

For the sake of completeness, here's another example how to install the environment system-wide.

```nix
{ # ...

  environment.systemPackages = with pkgs; [
    (python35.withPackages(ps: with ps; [ numpy toolz ]))
  ];
}
```

#### Temporary Python environment with `nix-shell`

The examples in the previous section showed how to install a Python environment
into a profile. For development you may need to use multiple environments.
`nix-shell` gives the possibility to temporarily load another environment, akin
to `virtualenv`.

There are two methods for loading a shell with Python packages. The first and recommended method
is to create an environment with `python.buildEnv` or `python.withPackages` and load that. E.g.
```sh
$ nix-shell -p 'python35.withPackages(ps: with ps; [ numpy toolz ])'
```
opens a shell from which you can launch the interpreter
```sh
[nix-shell:~] python3
```
The other method, which is not recommended, does not create an environment and requires you to list the packages directly,

```sh
$ nix-shell -p python35.pkgs.numpy python35.pkgs.toolz
```
Again, it is possible to launch the interpreter from the shell.
The Python interpreter has the attribute `pkgs` which contains all Python libraries for that specific interpreter.

##### Load environment from `.nix` expression
As explained in the Nix manual, `nix-shell` can also load an
expression from a `.nix` file. Say we want to have Python 3.5, `numpy`
and `toolz`, like before, in an environment. Consider a `shell.nix` file
with
```nix
with import <nixpkgs> {};

(python35.withPackages (ps: [ps.numpy ps.toolz])).env
```
Executing `nix-shell` gives you again a Nix shell from which you can run Python.

What's happening here?

1. We begin with importing the Nix Packages collections. `import <nixpkgs>` imports the `<nixpkgs>` function, `{}` calls it and the `with` statement brings all attributes of `nixpkgs` in the local scope. These attributes form the main package set.
2. Then we create a Python 3.5 environment with the `withPackages` function.
3. The `withPackages` function expects us to provide a function as an argument that takes the set of all python packages and returns a list of packages to include in the environment. Here, we select the packages `numpy` and `toolz` from the package set.

##### Execute command with `--run`
A convenient option with `nix-shell` is the `--run`
option, with which you can execute a command in the `nix-shell`. We can
e.g. directly open a Python shell
```sh
$ nix-shell -p python35Packages.numpy python35Packages.toolz --run "python3"
```
or run a script
```sh
$ nix-shell -p python35Packages.numpy python35Packages.toolz --run "python3 myscript.py"
```

##### `nix-shell` as shebang
In fact, for the second use case, there is a more convenient method. You can
add a [shebang](https://en.wikipedia.org/wiki/Shebang_(Unix)) to your script
specifying which dependencies `nix-shell` needs. With the following shebang, you
can just execute `./myscript.py`, and it will make available all dependencies and
run the script in the `python3` shell.

```py
#! /usr/bin/env nix-shell
#! nix-shell -i python3 -p "python3.withPackages(ps: [ps.numpy])"

import numpy

print(numpy.__version__)
```

### Developing with Python

Now that you know how to get a working Python environment with Nix, it is time
to go forward and start actually developing with Python. We will first have a
look at how Python packages are packaged on Nix. Then, we will look at how you
can use development mode with your code.

#### Packaging a library

With Nix all packages are built by functions. The main function in Nix for
building Python libraries is `buildPythonPackage`. Let's see how we can build the
`toolz` package.

```nix
{ lib, buildPythonPackage, fetchPypi }:

buildPythonPackage rec {
  pname = "toolz";
  version = "0.7.4";

  src = fetchPypi {
    inherit pname version;
    sha256 = "43c2c9e5e7a16b6c88ba3088a9bfc82f7db8e13378be7c78d6c14a5f8ed05afd";
  };

  doCheck = false;

  meta = with lib; {
    homepage = https://github.com/pytoolz/toolz;
    description = "List processing tools and functional utilities";
    license = licenses.bsd3;
    maintainers = with maintainers; [ fridh ];
  };
};
```

What happens here? The function `buildPythonPackage` is called and as argument
it accepts a set. In this case the set is a recursive set, `rec`. One of the
arguments is the name of the package, which consists of a basename (generally
following the name on PyPi) and a version. Another argument, `src` specifies the
source, which in this case is fetched from PyPI using the helper function
`fetchPypi`. The argument `doCheck` is used to set whether tests should be run
when building the package. Furthermore, we specify some (optional) meta
information. The output of the function is a derivation.

An expression for `toolz` can be found in the Nixpkgs repository. As explained
in the introduction of this Python section, a derivation of `toolz` is available
for each interpreter version, e.g. `python35.pkgs.toolz` refers to the `toolz`
derivation corresponding to the CPython 3.5 interpreter.
The above example works when you're directly working on
`pkgs/top-level/python-packages.nix` in the Nixpkgs repository. Often though,
you will want to test a Nix expression outside of the Nixpkgs tree.

The following expression creates a derivation for the `toolz` package,
and adds it along with a `numpy` package to a Python environment.

```nix
with import <nixpkgs> {};

( let
    my_toolz = python35.pkgs.buildPythonPackage rec {
      pname = "toolz";
      version = "0.7.4";

      src = python35.pkgs.fetchPypi {
        inherit pname version;
        sha256 = "43c2c9e5e7a16b6c88ba3088a9bfc82f7db8e13378be7c78d6c14a5f8ed05afd";
      };

      doCheck = false;

      meta = {
        homepage = "https://github.com/pytoolz/toolz/";
        description = "List processing tools and functional utilities";
      };
    };

  in python35.withPackages (ps: [ps.numpy my_toolz])
).env
```
Executing `nix-shell` will result in an environment in which you can use
Python 3.5 and the `toolz` package. As you can see we had to explicitly mention
for which Python version we want to build a package.

So, what did we do here? Well, we took the Nix expression that we used earlier
to build a Python environment, and said that we wanted to include our own
version of `toolz`, named `my_toolz`. To introduce our own package in the scope
of `withPackages` we used a `let` expression. You can see that we used
`ps.numpy` to select numpy from the nixpkgs package set (`ps`). We did not take
`toolz` from the Nixpkgs package set this time, but instead took our own version
that we introduced with the `let` expression.

#### Handling dependencies

Our example, `toolz`, does not have any dependencies on other Python packages or
system libraries. According to the manual, `buildPythonPackage` uses the
arguments `buildInputs` and `propagatedBuildInputs` to specify dependencies. If
something is exclusively a build-time dependency, then the dependency should be
included as a `buildInput`, but if it is (also) a runtime dependency, then it
should be added to `propagatedBuildInputs`. Test dependencies are considered
build-time dependencies and passed to `checkInputs`.

The following example shows which arguments are given to `buildPythonPackage` in
order to build [`datashape`](https://github.com/blaze/datashape).

```nix
{ # ...

  datashape = buildPythonPackage rec {
    pname = "datashape";
    version = "0.4.7";

    src = fetchPypi {
      inherit pname version;
      sha256 = "14b2ef766d4c9652ab813182e866f493475e65e558bed0822e38bf07bba1a278";
    };

    checkInputs = with self; [ pytest ];
    propagatedBuildInputs = with self; [ numpy multipledispatch dateutil ];

    meta = with lib; {
      homepage = https://github.com/ContinuumIO/datashape;
      description = "A data description language";
      license = licenses.bsd2;
      maintainers = with maintainers; [ fridh ];
    };
  };
}
```

We can see several runtime dependencies, `numpy`, `multipledispatch`, and
`dateutil`. Furthermore, we have one `buildInput`, i.e. `pytest`. `pytest` is a
test runner and is only used during the `checkPhase` and is therefore not added
to `propagatedBuildInputs`.

In the previous case we had only dependencies on other Python packages to consider.
Occasionally you have also system libraries to consider. E.g., `lxml` provides
Python bindings to `libxml2` and `libxslt`. These libraries are only required
when building the bindings and are therefore added as `buildInputs`.

```nix
{ # ...

  lxml = buildPythonPackage rec {
    pname = "lxml";
    version = "3.4.4";

    src = fetchPypi {
      inherit pname version;
      sha256 = "16a0fa97hym9ysdk3rmqz32xdjqmy4w34ld3rm3jf5viqjx65lxk";
    };

    buildInputs = with self; [ pkgs.libxml2 pkgs.libxslt ];

    meta = with lib; {
      description = "Pythonic binding for the libxml2 and libxslt libraries";
      homepage = https://lxml.de;
      license = licenses.bsd3;
      maintainers = with maintainers; [ sjourdois ];
    };
  };
}
```

In this example `lxml` and Nix are able to work out exactly where the relevant
files of the dependencies are. This is not always the case.

The example below shows bindings to The Fastest Fourier Transform in the West, commonly known as
FFTW. On Nix we have separate packages of FFTW for the different types of floats
(`"single"`, `"double"`, `"long-double"`). The bindings need all three types,
and therefore we add all three as `buildInputs`. The bindings don't expect to
find each of them in a different folder, and therefore we have to set `LDFLAGS`
and `CFLAGS`.

```nix
{ # ...

  pyfftw = buildPythonPackage rec {
    pname = "pyFFTW";
    version = "0.9.2";

    src = fetchPypi {
      inherit pname version;
      sha256 = "f6bbb6afa93085409ab24885a1a3cdb8909f095a142f4d49e346f2bd1b789074";
    };

    buildInputs = [ pkgs.fftw pkgs.fftwFloat pkgs.fftwLongDouble];

    propagatedBuildInputs = with self; [ numpy scipy ];

    # Tests cannot import pyfftw. pyfftw works fine though.
    doCheck = false;

    preConfigure = ''
      export LDFLAGS="-L${pkgs.fftw.dev}/lib -L${pkgs.fftwFloat.out}/lib -L${pkgs.fftwLongDouble.out}/lib"
      export CFLAGS="-I${pkgs.fftw.dev}/include -I${pkgs.fftwFloat.dev}/include -I${pkgs.fftwLongDouble.dev}/include"
    '';

    meta = with lib; {
      description = "A pythonic wrapper around FFTW, the FFT library, presenting a unified interface for all the supported transforms";
      homepage = http://hgomersall.github.com/pyFFTW;
      license = with licenses; [ bsd2 bsd3 ];
      maintainers = with maintainers; [ fridh ];
    };
  };
}
```
Note also the line `doCheck = false;`, we explicitly disabled running the test-suite.


#### Develop local package

As a Python developer you're likely aware of [development mode](http://setuptools.readthedocs.io/en/latest/setuptools.html#development-mode) (`python setup.py develop`);
instead of installing the package this command creates a special link to the project code.
That way, you can run updated code without having to reinstall after each and every change you make.
Development mode is also available. Let's see how you can use it.

In the previous Nix expression the source was fetched from an url. We can also refer to a local source instead using
`src = ./path/to/source/tree;`

If we create a `shell.nix` file which calls `buildPythonPackage`, and if `src`
is a local source, and if the local source has a `setup.py`, then development
mode is activated.

In the following example we create a simple environment that
has a Python 3.5 version of our package in it, as well as its dependencies and
other packages we like to have in the environment, all specified with `propagatedBuildInputs`.
Indeed, we can just add any package we like to have in our environment to `propagatedBuildInputs`.

```nix
with import <nixpkgs> {};
with pkgs.python35Packages;

buildPythonPackage rec {
  name = "mypackage";
  src = ./path/to/package/source;
  propagatedBuildInputs = [ pytest numpy pkgs.libsndfile ];
}
```

It is important to note that due to how development mode is implemented on Nix it is not possible to have multiple packages simultaneously in development mode.


### Organising your packages

So far we discussed how you can use Python on Nix, and how you can develop with
it. We've looked at how you write expressions to package Python packages, and we
looked at how you can create environments in which specified packages are
available.

At some point you'll likely have multiple packages which you would
like to be able to use in different projects. In order to minimise unnecessary
duplication we now look at how you can maintain a repository with your
own packages. The important functions here are `import` and `callPackage`.

### Including a derivation using `callPackage`

Earlier we created a Python environment using `withPackages`, and included the
`toolz` package via a `let` expression.
Let's split the package definition from the environment definition.

We first create a function that builds `toolz` in `~/path/to/toolz/release.nix`

```nix
{ lib, pkgs, buildPythonPackage }:

buildPythonPackage rec {
  pname = "toolz";
  version = "0.7.4";

  src = fetchPypi {
    inherit pname version;
    sha256 = "43c2c9e5e7a16b6c88ba3088a9bfc82f7db8e13378be7c78d6c14a5f8ed05afd";
  };

  meta = with lib; {
    homepage = "http://github.com/pytoolz/toolz/";
    description = "List processing tools and functional utilities";
    license = licenses.bsd3;
    maintainers = with maintainers; [ fridh ];
  };
}
```

It takes two arguments, `pkgs` and `buildPythonPackage`.
We now call this function using `callPackage` in the definition of our environment

```nix
with import <nixpkgs> {};

( let
    toolz = pkgs.callPackage /path/to/toolz/release.nix {
      pkgs = pkgs;
      buildPythonPackage = pkgs.python35Packages.buildPythonPackage;
    };
  in pkgs.python35.withPackages (ps: [ ps.numpy toolz ])
).env
```

Important to remember is that the Python version for which the package is made
depends on the `python` derivation that is passed to `buildPythonPackage`. Nix
tries to automatically pass arguments when possible, which is why generally you
don't explicitly define which `python` derivation should be used. In the above
example we use `buildPythonPackage` that is part of the set `python35Packages`,
and in this case the `python35` interpreter is automatically used.

## Reference

### Interpreters

Versions 2.7, 3.5, 3.6 and 3.7 of the CPython interpreter are available as
respectively `python27`, `python35`, `python36` and `python37`. The aliases
`python2` and `python3` correspond to respectively `python27` and
`python37`. The default interpreter, `python`, maps to `python2`. The PyPy
interpreters compatible with Python 2.7 and 3 are available as `pypy27` and
`pypy3`, with aliases `pypy2` mapping to `pypy27` and `pypy` mapping to
`pypy2`. The Nix expressions for the interpreters can be
found in `pkgs/development/interpreters/python`.

All packages depending on any Python interpreter get appended
`out/{python.sitePackages}` to `$PYTHONPATH` if such directory
exists.

#### Missing `tkinter` module standard library

To reduce closure size the `Tkinter`/`tkinter` is available as a separate package, `pythonPackages.tkinter`.

#### Attributes on interpreters packages

Each interpreter has the following attributes:

- `libPrefix`. Name of the folder in `${python}/lib/` for corresponding interpreter.
- `interpreter`. Alias for `${python}/bin/${executable}`.
- `buildEnv`. Function to build python interpreter environments with extra packages bundled together. See section *python.buildEnv function* for usage and documentation.
- `withPackages`. Simpler interface to `buildEnv`. See section *python.withPackages function* for usage and documentation.
- `sitePackages`. Alias for `lib/${libPrefix}/site-packages`.
- `executable`. Name of the interpreter executable, e.g. `python3.7`.
- `pkgs`. Set of Python packages for that specific interpreter. The package set can be modified by overriding the interpreter and passing `packageOverrides`.

### Building packages and applications

Python libraries and applications that use `setuptools` or
`distutils` are typically build with respectively the `buildPythonPackage` and
`buildPythonApplication` functions. These two functions also support installing a `wheel`.

All Python packages reside in `pkgs/top-level/python-packages.nix` and all
applications elsewhere. In case a package is used as both a library and an application,
then the package should be in `pkgs/top-level/python-packages.nix` since only those packages are made
available for all interpreter versions. The preferred location for library expressions is in
`pkgs/development/python-modules`. It is important that these packages are
called from `pkgs/top-level/python-packages.nix` and not elsewhere, to guarantee
the right version of the package is built.

Based on the packages defined in `pkgs/top-level/python-packages.nix` an
attribute set is created for each available Python interpreter. The available
sets are

* `pkgs.python27Packages`
* `pkgs.python35Packages`
* `pkgs.python36Packages`
* `pkgs.python37Packages`
* `pkgs.pypyPackages`

and the aliases

* `pkgs.python2Packages` pointing to `pkgs.python27Packages`
* `pkgs.python3Packages` pointing to `pkgs.python37Packages`
* `pkgs.pythonPackages` pointing to `pkgs.python2Packages`

#### `buildPythonPackage` function

The `buildPythonPackage` function is implemented in
`pkgs/development/interpreters/python/build-python-package.nix`

The following is an example:
```nix
{ lib, buildPythonPackage, fetchPypi, hypothesis, setuptools_scm, attrs, py, setuptools, six, pluggy }:

buildPythonPackage rec {
  pname = "pytest";
  version = "3.3.1";

  src = fetchPypi {
    inherit pname version;
    sha256 = "cf8436dc59d8695346fcd3ab296de46425ecab00d64096cebe79fb51ecb2eb93";
  };

  postPatch = ''
    # don't test bash builtins
    rm testing/test_argcomplete.py
  '';

  checkInputs = [ hypothesis ];
  buildInputs = [ setuptools_scm ];
  propagatedBuildInputs = [ attrs py setuptools six pluggy ];

  meta = with lib; {
    maintainers = with maintainers; [ domenkozar lovek323 madjar lsix ];
    description = "Framework for writing tests";
  };
}
```

The `buildPythonPackage` mainly does four things:

* In the `buildPhase`, it calls `${python.interpreter} setup.py bdist_wheel` to
  build a wheel binary zipfile.
* In the `installPhase`, it installs the wheel file using `pip install *.whl`.
* In the `postFixup` phase, the `wrapPythonPrograms` bash function is called to
  wrap all programs in the `$out/bin/*` directory to include `$PATH`
  environment variable and add dependent libraries to script's `sys.path`.
* In the `installCheck` phase, `${python.interpreter} setup.py test` is ran.

As in Perl, dependencies on other Python packages can be specified in the
`buildInputs` and `propagatedBuildInputs` attributes.  If something is
exclusively a build-time dependency, use `buildInputs`; if it is (also) a runtime
dependency, use `propagatedBuildInputs`.

By default tests are run because `doCheck = true`. Test dependencies, like
e.g. the test runner, should be added to `checkInputs`.

By default `meta.platforms` is set to the same value
as the interpreter unless overridden otherwise.

##### `buildPythonPackage` parameters

All parameters from `stdenv.mkDerivation` function are still supported. The following are specific to `buildPythonPackage`:

* `catchConflicts ? true`: If `true`, abort package build if a package name appears more than once in dependency tree. Default is `true`.
* `disabled` ? false: If `true`, package is not build for the particular Python interpreter version.
* `dontWrapPythonPrograms ? false`: Skip wrapping of python programs.
* `installFlags ? []`: A list of strings. Arguments to be passed to `pip install`. To pass options to `python setup.py install`, use `--install-option`. E.g., `installFlags=["--install-option='--cpp_implementation'"]`.
* `format ? "setuptools"`: Format of the source. Valid options are `"setuptools"`, `"pyproject"`, `"flit"`, `"wheel"`, and `"other"`. `"setuptools"` is for when the source has a `setup.py` and `setuptools` is used to build a wheel, `flit`, in case `flit` should be used to build a wheel, and `wheel` in case a wheel is provided. Use `other` when a custom `buildPhase` and/or `installPhase` is needed.
* `makeWrapperArgs ? []`: A list of strings. Arguments to be passed to `makeWrapper`, which wraps generated binaries. By default, the arguments to `makeWrapper` set `PATH` and `PYTHONPATH` environment variables before calling the binary. Additional arguments here can allow a developer to set environment variables which will be available when the binary is run. For example, `makeWrapperArgs = ["--set FOO BAR" "--set BAZ QUX"]`.
* `namePrefix`: Prepends text to `${name}` parameter. In case of libraries, this defaults to `"python3.5-"` for Python 3.5, etc., and in case of applications to `""`.
* `pythonPath ? []`: List of packages to be added into `$PYTHONPATH`. Packages in `pythonPath` are not propagated (contrary to `propagatedBuildInputs`).
* `preShellHook`: Hook to execute commands before `shellHook`.
* `postShellHook`: Hook to execute commands after `shellHook`.
* `removeBinByteCode ? true`: Remove bytecode from `/bin`. Bytecode is only created when the filenames end with `.py`.
* `setupPyBuildFlags ? []`: List of flags passed to `setup.py build_ext` command.

The `stdenv.mkDerivation` function accepts various parameters for describing build inputs (see "Specifying dependencies"). The following are of special
interest for Python packages, either because these are primarily used, or because their behaviour is different:

* `nativeBuildInputs ? []`: Build-time only dependencies. Typically executables as well as the items listed in `setup_requires`.
* `buildInputs ? []`: Build and/or run-time dependencies that need to be be compiled for the host machine. Typically non-Python libraries which are being linked.
* `checkInputs ? []`: Dependencies needed for running the `checkPhase`. These are added to `nativeBuildInputs` when `doCheck = true`. Items listed in `tests_require` go here.
* `propagatedBuildInputs ? []`: Aside from propagating dependencies, `buildPythonPackage` also injects code into and wraps executables with the paths included in this list. Items listed in `install_requires` go here.

##### Overriding Python packages

The `buildPythonPackage` function has a `overridePythonAttrs` method that
can be used to override the package. In the following example we create an
environment where we have the `blaze` package using an older version of `pandas`.
We override first the Python interpreter and pass
`packageOverrides` which contains the overrides for packages in the package set.

```nix
with import <nixpkgs> {};

(let
  python = let
    packageOverrides = self: super: {
      pandas = super.pandas.overridePythonAttrs(old: rec {
        version = "0.19.1";
        src =  super.fetchPypi {
          pname = "pandas";
          inherit version;
          sha256 = "08blshqj9zj1wyjhhw3kl2vas75vhhicvv72flvf1z3jvapgw295";
        };
      });
    };
  in pkgs.python3.override {inherit packageOverrides;};

in python.withPackages(ps: [ps.blaze])).env
```

#### `buildPythonApplication` function

The `buildPythonApplication` function is practically the same as
`buildPythonPackage`. The main purpose of this function is to build a Python
package where one is interested only in the executables, and not importable
modules. For that reason, when adding this package to a `python.buildEnv`, the
modules won't be made available.

Another difference is that `buildPythonPackage` by default prefixes the names of
the packages with the version of the interpreter. Because this is irrelevant for
applications, the prefix is omitted.

When packaging a python application with `buildPythonApplication`, it should be
called with `callPackage` and passed `python` or `pythonPackages` (possibly
specifying an interpreter version), like this:

```nix
{ lib, python3Packages }:

python3Packages.buildPythonApplication rec {
  pname = "luigi";
  version = "2.7.9";

  src = python3Packages.fetchPypi {
    inherit pname version;
    sha256 = "035w8gqql36zlan0xjrzz9j4lh9hs0qrsgnbyw07qs7lnkvbdv9x";
  };

  propagatedBuildInputs = with python3Packages; [ tornado_4 python-daemon ];

  meta = with lib; {
    ...
  };
}
```

This is then added to `all-packages.nix` just as any other application would be.

```nix
luigi = callPackage ../applications/networking/cluster/luigi { };
```

Since the package is an application, a consumer doesn't need to care about
python versions or modules, which is why they don't go in `pythonPackages`.

#### `toPythonApplication` function

A distinction is made between applications and libraries, however, sometimes a
package is used as both. In this case the package is added as a library to
`python-packages.nix` and as an application to `all-packages.nix`. To reduce
duplication the `toPythonApplication` can be used to convert a library to an
application.

The Nix expression shall use `buildPythonPackage` and be called from
`python-packages.nix`. A reference shall be created from `all-packages.nix` to
the attribute in `python-packages.nix`, and the `toPythonApplication` shall be
applied to the reference:
```nix
youtube-dl = with pythonPackages; toPythonApplication youtube-dl;
```

#### `toPythonModule` function

In some cases, such as bindings, a package is created using
`stdenv.mkDerivation` and added as attribute in `all-packages.nix`.
The Python bindings should be made available from `python-packages.nix`.
The `toPythonModule` function takes a derivation and makes certain Python-specific modifications.
```nix
opencv = toPythonModule (pkgs.opencv.override {
  enablePython = true;
  pythonPackages = self;
});
```
Do pay attention to passing in the right Python version!

#### `python.buildEnv` function

Python environments can be created using the low-level `pkgs.buildEnv` function.
This example shows how to create an environment that has the Pyramid Web Framework.
Saving the following as `default.nix`
```nix
with import <nixpkgs> {};

python.buildEnv.override {
  extraLibs = [ pkgs.pythonPackages.pyramid ];
  ignoreCollisions = true;
}
```

and running `nix-build` will create
```
/nix/store/cf1xhjwzmdki7fasgr4kz6di72ykicl5-python-2.7.8-env
```

with wrapped binaries in `bin/`.

You can also use the `env` attribute to create local environments with needed
packages installed. This is somewhat comparable to `virtualenv`. For example,
running `nix-shell` with the following `shell.nix`
```nix
with import <nixpkgs> {};

(python3.buildEnv.override {
  extraLibs = with python3Packages; [ numpy requests ];
}).env
```

will drop you into a shell where Python will have the
specified packages in its path.


##### `python.buildEnv` arguments

* `extraLibs`: List of packages installed inside the environment.
* `postBuild`: Shell command executed after the build of environment.
* `ignoreCollisions`: Ignore file collisions inside the environment (default is `false`).

#### `python.withPackages` function

The `python.withPackages` function provides a simpler interface to the `python.buildEnv` functionality.
It takes a function as an argument that is passed the set of python packages and returns the list
of the packages to be included in the environment. Using the `withPackages` function, the previous
example for the Pyramid Web Framework environment can be written like this:
```nix
with import <nixpkgs> {};

python.withPackages (ps: [ps.pyramid])
```

`withPackages` passes the correct package set for the specific interpreter version as an
argument to the function. In the above example, `ps` equals `pythonPackages`.
But you can also easily switch to using python3:
```nix
with import <nixpkgs> {};

python3.withPackages (ps: [ps.pyramid])
```

Now, `ps` is set to `python3Packages`, matching the version of the interpreter.

As `python.withPackages` simply uses `python.buildEnv` under the hood, it also supports the `env`
attribute. The `shell.nix` file from the previous section can thus be also written like this:
```nix
with import <nixpkgs> {};

(python36.withPackages (ps: [ps.numpy ps.requests])).env
```

In contrast to `python.buildEnv`, `python.withPackages` does not support the more advanced options
such as `ignoreCollisions = true` or `postBuild`. If you need them, you have to use `python.buildEnv`.

Python 2 namespace packages may provide `__init__.py` that collide. In that case `python.buildEnv`
should be used with `ignoreCollisions = true`.

### Development mode

Development or editable mode is supported. To develop Python packages
`buildPythonPackage` has additional logic inside `shellPhase` to run `pip
install -e . --prefix $TMPDIR/`for the package.

Warning: `shellPhase` is executed only if `setup.py` exists.

Given a `default.nix`:
```nix
with import <nixpkgs> {};

buildPythonPackage { name = "myproject";

buildInputs = with pkgs.pythonPackages; [ pyramid ];

src = ./.; }
```

Running `nix-shell` with no arguments should give you
the environment in which the package would be built with
`nix-build`.

Shortcut to setup environments with C headers/libraries and python packages:
```shell
nix-shell -p pythonPackages.pyramid zlib libjpeg git
```

Note: There is a boolean value `lib.inNixShell` set to `true` if nix-shell is invoked.

### Tools

Packages inside nixpkgs are written by hand. However many tools exist in
community to help save time. No tool is preferred at the moment.

- [python2nix](https://github.com/proger/python2nix) by Vladimir Kirillov
- [pypi2nix](https://github.com/garbas/pypi2nix) by Rok Garbas
- [pypi2nix](https://github.com/offlinehacker/pypi2nix) by Jaka Hudoklin

### Deterministic builds

The Python interpreters are now built deterministically.
Minor modifications had to be made to the interpreters in order to generate
deterministic bytecode. This has security implications and is relevant for
those using Python in a `nix-shell`.

When the environment variable `DETERMINISTIC_BUILD` is set, all bytecode will have timestamp 1.
The `buildPythonPackage` function sets `DETERMINISTIC_BUILD=1` and
[PYTHONHASHSEED=0](https://docs.python.org/3.5/using/cmdline.html#envvar-PYTHONHASHSEED).
Both are also exported in `nix-shell`.


### Automatic tests

It is recommended to test packages as part of the build process.
Source distributions (`sdist`) often include test files, but not always.

By default the command `python setup.py test` is run as part of the
`checkPhase`, but often it is necessary to pass a custom `checkPhase`. An
example of such a situation is when `py.test` is used.

#### Common issues

- Non-working tests can often be deselected. By default `buildPythonPackage` runs `python setup.py test`.
  Most python modules follows the standard test protocol where the pytest runner can be used instead.
  `py.test` supports a `-k` parameter to ignore test methods or classes:

  ```nix
  buildPythonPackage {
    # ...
    # assumes the tests are located in tests
    checkInputs = [ pytest ];
    checkPhase = ''
      py.test -k 'not function_name and not other_function' tests
    '';
  }
  ```
- Tests that attempt to access `$HOME` can be fixed by using the following work-around before running tests (e.g. `preCheck`): `export HOME=$(mktemp -d)`

## FAQ

### How to solve circular dependencies?

Consider the packages `A` and `B` that depend on each other. When packaging `B`,
a solution is to override package `A` not to depend on `B` as an input. The same
should also be done when packaging `A`.

### How to override a Python package?

We can override the interpreter and pass `packageOverrides`.
In the following example we rename the `pandas` package and build it.
```nix
with import <nixpkgs> {};

(let
  python = let
    packageOverrides = self: super: {
      pandas = super.pandas.overridePythonAttrs(old: {name="foo";});
    };
  in pkgs.python35.override {inherit packageOverrides;};

in python.withPackages(ps: [ps.pandas])).env
```
Using `nix-build` on this expression will build an environment that contains the
package `pandas` but with the new name `foo`.

All packages in the package set will use the renamed package.
A typical use case is to switch to another version of a certain package.
For example, in the Nixpkgs repository we have multiple versions of `django` and `scipy`.
In the following example we use a different version of `scipy` and create an environment that uses it.
All packages in the Python package set will now use the updated `scipy` version.

```nix
with import <nixpkgs> {};

( let
    packageOverrides = self: super: {
      scipy = super.scipy_0_17;
    };
  in (pkgs.python35.override {inherit packageOverrides;}).withPackages (ps: [ps.blaze])
).env
```
The requested package `blaze` depends on `pandas` which itself depends on `scipy`.

If you want the whole of Nixpkgs to use your modifications, then you can use `overlays`
as explained in this manual. In the following example we build a `inkscape` using a different version of `numpy`.
```nix
let
  pkgs = import <nixpkgs> {};
  newpkgs = import pkgs.path { overlays = [ (pkgsself: pkgssuper: {
    python27 = let
      packageOverrides = self: super: {
        numpy = super.numpy_1_10;
      };
    in pkgssuper.python27.override {inherit packageOverrides;};
  } ) ]; };
in newpkgs.inkscape
```

### `python setup.py bdist_wheel` cannot create .whl

Executing `python setup.py bdist_wheel` in a `nix-shell `fails with
```
ValueError: ZIP does not support timestamps before 1980
```

This is because files from the Nix store (which have a timestamp of the UNIX epoch of January 1, 1970) are included in the .ZIP, but .ZIP archives follow the DOS convention of counting timestamps from 1980.

The command `bdist_wheel` reads the `SOURCE_DATE_EPOCH` environment variable, which `nix-shell` sets to 1. Unsetting this variable or giving it a value corresponding to 1980 or later enables building wheels.

Use 1980 as timestamp:
```shell
nix-shell --run "SOURCE_DATE_EPOCH=315532800 python3 setup.py bdist_wheel"
```
or the current time:
```shell
nix-shell --run "SOURCE_DATE_EPOCH=$(date +%s) python3 setup.py bdist_wheel"
```
or unset `SOURCE_DATE_EPOCH`:
```shell
nix-shell --run "unset SOURCE_DATE_EPOCH; python3 setup.py bdist_wheel"
```

### `install_data` / `data_files` problems

If you get the following error:
```
could not create '/nix/store/6l1bvljpy8gazlsw2aw9skwwp4pmvyxw-python-2.7.8/etc':
Permission denied
```
This is a [known bug](https://github.com/pypa/setuptools/issues/130) in `setuptools`.
Setuptools `install_data` does not respect `--prefix`. An example of such package using the feature is `pkgs/tools/X11/xpra/default.nix`.
As workaround install it as an extra `preInstall` step:
```shell
${python.interpreter} setup.py install_data --install-dir=$out --root=$out
sed -i '/ = data\_files/d' setup.py
```

###  Rationale of non-existent global site-packages

On most operating systems a global `site-packages` is maintained. This however
becomes problematic if you want to run multiple Python versions or have multiple
versions of certain libraries for your projects. Generally, you would solve such
issues by creating virtual environments using `virtualenv`.

On Nix each package has an isolated dependency tree which, in the case of
Python, guarantees the right versions of the interpreter and libraries or
packages are available. There is therefore no need to maintain a global `site-packages`.

If you want to create a Python environment for development, then the recommended
method is to use `nix-shell`, either with or without the `python.buildEnv`
function.

### How to consume python modules using pip in a virtualenv like I am used to on other Operating Systems ?

This is an example of a `default.nix` for a `nix-shell`, which allows to consume a `virtualenv` environment,
and install python modules through `pip` the traditional way.

Create this `default.nix` file, together with a `requirements.txt` and simply execute `nix-shell`.

```nix
with import <nixpkgs> {};
with pkgs.python27Packages;

stdenv.mkDerivation {
  name = "impurePythonEnv";
  buildInputs = [
    # these packages are required for virtualenv and pip to work:
    #
    python27Full
    python27Packages.virtualenv
    python27Packages.pip
    # the following packages are related to the dependencies of your python
    # project.
    # In this particular example the python modules listed in the
    # requirements.txt require the following packages to be installed locally
    # in order to compile any binary extensions they may require.
    #
    taglib
    openssl
    git
    libxml2
    libxslt
    libzip
    stdenv
    zlib ];
  src = null;
  shellHook = ''
  # set SOURCE_DATE_EPOCH so that we can use python wheels
  SOURCE_DATE_EPOCH=$(date +%s)
  virtualenv --no-setuptools venv
  export PATH=$PWD/venv/bin:$PATH
  pip install -r requirements.txt
  '';
}
```

Note that the `pip install` is an imperative action. So every time `nix-shell`
is executed it will attempt to download the python modules listed in
requirements.txt. However these will be cached locally within the `virtualenv`
folder and not downloaded again.

### How to override a Python package from `configuration.nix`?

If you need to change a package's attribute(s) from `configuration.nix` you could do:

```nix
  nixpkgs.config.packageOverrides = super: {
    python = super.python.override {
      packageOverrides = python-self: python-super: {
        zerobin = python-super.zerobin.overrideAttrs (oldAttrs: {
          src = super.fetchgit {
            url = "https://github.com/sametmax/0bin";
            rev = "a344dbb18fe7a855d0742b9a1cede7ce423b34ec";
            sha256 = "16d769kmnrpbdr0ph0whyf4yff5df6zi4kmwx7sz1d3r6c8p6xji";
          };
        });
      };
    };
  };
```

`pythonPackages.zerobin` is now globally overridden. All packages and also the
`zerobin` NixOS service use the new definition.
Note that `python-super` refers to the old package set and `python-self`
to the new, overridden version.

To modify only a Python package set instead of a whole Python derivation, use this snippet:

```nix
  myPythonPackages = pythonPackages.override {
    overrides = self: super: {
      zerobin = ...;
    };
  }
```

### How to override a Python package using overlays?

Use the following overlay template:

```nix
self: super: {
  python = super.python.override {
    packageOverrides = python-self: python-super: {
      zerobin = python-super.zerobin.overrideAttrs (oldAttrs: {
        src = super.fetchgit {
          url = "https://github.com/sametmax/0bin";
          rev = "a344dbb18fe7a855d0742b9a1cede7ce423b34ec";
          sha256 = "16d769kmnrpbdr0ph0whyf4yff5df6zi4kmwx7sz1d3r6c8p6xji";
        };
      });
    };
  };
}
```

### How to use Intel's MKL with numpy and scipy?

A `site.cfg` is created that configures BLAS based on the `blas` parameter
of the `numpy` derivation. By passing in `mkl`, `numpy` and packages depending
on `numpy` will be built with `mkl`.

The following is an overlay that configures `numpy` to use `mkl`:
```nix
self: super: {
  python37 = super.python37.override {
    packageOverrides = python-self: python-super: {
      numpy = python-super.numpy.override {
        blas = super.pkgs.mkl;
      };
    };
  };
}
```

`mkl` requires an `openmp` implementation when running with multiple processors.
By default, `mkl` will use Intel's `iomp` implementation if no other is
specified, but this is a runtime-only dependency and binary compatible with the
LLVM implementation. To use that one instead, Intel recommends users set it with
`LD_PRELOAD`.

Note that `mkl` is only available on `x86_64-{linux,darwin}` platforms;
moreover, Hydra is not building and distributing pre-compiled binaries using it.

### What inputs do `setup_requires`, `install_requires` and `tests_require` map to?

In a `setup.py` or `setup.cfg` it is common to declare dependencies:

* `setup_requires` corresponds to `nativeBuildInputs`
* `install_requires` corresponds to `propagatedBuildInputs`
* `tests_require` corresponds to `checkInputs`

## Contributing

### Contributing guidelines

Following rules are desired to be respected:

* Python libraries are called from `python-packages.nix` and packaged with `buildPythonPackage`. The expression of a library should be in `pkgs/development/python-modules/<name>/default.nix`. Libraries in `pkgs/top-level/python-packages.nix` are sorted quasi-alphabetically to avoid merge conflicts.
* Python applications live outside of `python-packages.nix` and are packaged with `buildPythonApplication`.
* Make sure libraries build for all Python interpreters.
* By default we enable tests. Make sure the tests are found and, in the case of libraries, are passing for all interpreters. If certain tests fail they can be disabled individually. Try to avoid disabling the tests altogether. In any case, when you disable tests, leave a comment explaining why.
* Commit names of Python libraries should reflect that they are Python libraries, so write for example `pythonPackages.numpy: 1.11 -> 1.12`.
* Attribute names in `python-packages.nix` should be normalized according to [PEP 0503](https://www.python.org/dev/peps/pep-0503/#normalized-names).
  This means that characters should be converted to lowercase and `.` and `_` should be replaced by a single `-` (foo-bar-baz instead of Foo__Bar.baz )